Cardiac arrhythmia is a condition in which the electrical activity of the heart is irregular or faster or slower than normal. Cardiac arrhythmia may be classified by rate and/or mechanism. For instance, atrial fibrillation (AF) is the most common type of serious arrhythmia that involves a very fast and irregular contraction of the atria. Ventricular fibrillation (VF) is a condition in which there is uncoordinated contraction of the cardiac muscle of the ventricles in the heart. Myocardial ischemia is a type of arrhythmia that occurs when blood flow to the heart muscle is decreased by a partial or complete blockage of the heart's arteries. Myocardial infarction (commonly known as a heart attack) occurs when blood stops flowing properly to part of the heart and the heart muscle is injured due to not receiving enough oxygen. This can lead to irreversible scarring and necrosis of the muscle tissue, reducing the efficiency with which the heart can pump blood to the rest of the body and possibly leading to fatal cardiac arrhythmia.
Cardiac functional abnormality and arrhythmia usually slow down tissue performance (e.g., contracting and reperfusion) and reduce blood flow to regions of the heart. Cells respond by altering the action potentials. The changes in these individual cells manifest in electrograms during depolarization and repolarization, reducing signal energy (hyperkalemia or anoxia) or creating multi-phasic waveform, particularly distortions in the electrophysiological response morphology. Electrophysiological (EP) response and activity analysis is routinely used to manage such cardiac arrhythmias, disorders and irregularities. The 12-lead electrocardiogram (ECG) and multi-channel intra-cardiac electrograms (ICEG) are generally regarded as the diagnostic reference standard for evaluating cardiac rhythm and events.
Early myocardial ischemia and infarction (MI) analysis and characterization are critical for the management of cardiac disorders and irregularities. Usually, surface ECG signal analyses based on electrophysiological activity waveforms (e.g., ECG signals and intra-cardiac electrograms) and time domain parameters (e.g., magnitude voltage) of the waveforms are utilized for detecting cardiac arrhythmia and diagnosing pathology. Known systems use ECG waveform analysis of a P wave, QRS complex, ST segment and T wave, to monitor and identify cardiac arrhythmia.
However, known methods based on waveform morphology and time domain parameter analysis are often subjective and time-consuming, and require expertise and clinical experience for accurate interpretation and proper cardiac rhythm management. Known systems typically fail to provide sufficient information on cardiac electrophysiological function/activity interpretation, tissue mapping and arrhythmia localization. Additionally, known cardiac detection methods often focus on time (e.g., amplitude, latency) or frequency (e.g., power, spectrum) domain changes in an ECG signal, which may not detect small signal changes that are usually invisible in a signal wave morphology display. Further, known systems fail to provide quantitative clinical evaluation of myocardial ischemia events.
Accordingly, there exists a need to provide an improved framework to address these deficiencies and related problems.